Three-Dimensional Upper Limb Movement Decoding from EEG Signals

被引:0
|
作者
Kim, Jeong-Hun [1 ]
Chavarriaga, Ricardo [2 ]
Millan, Jose del R. [2 ]
Lee, Seong-Whan [1 ]
机构
[1] Korea Univ, Dept Brain & Cognit Engn, Seoul, South Korea
[2] Ecole Polytech Fed Lausanne, Defitech Chair Noninvas Brain Machine Interface, Lausanne, Switzerland
基金
新加坡国家研究基金会;
关键词
BCI; Arm movement trajectory; EEG; Upper limb rehabilitation;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A brain-computer interface (BCI) can be used to control a limb neuroprosthesis in patients. In particular, decoding trajectory of upper limb with motor imagery (MI) can support motor rehabilitation using a wearable robotic arm. Recent research shows the possibility of decoding hand movement trajectory from electroencephalography (EEG) signals. However, such studies are insufficient to apply motor rehabilitation, which are only considered hand movement trajectory. Although disabilities patients take correct hand movement, sometimes wrong elbow movement can be taken in motor rehabilitation. In this study, we explore to decode velocity of both hand and elbow at the same time from EEG signals when subjects move upper limb. The result shows feasibility toward controlling robotic arm.
引用
收藏
页码:109 / 111
页数:3
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